This got me thinking – what exactly do my followers want to see from me? What do they expect to see from me? Can this be determined, and if so, can this data be used by other people to figure out what their followers want from them, too?

My Twitter Social Experiment

I decided to spend that weekend submitting 50 tweets contained a variety of linked content to my followers and then tracking the results using Bit.ly. From this, I hoped to determine:

I would have liked to have done more topics, and with hindsight I wish I’d have included subjects such as science and sports.

Where appropriate, I would mark the tweets accordingly (i.e., ‘video’ or ‘funny’). All affiliate links were through Amazon.com, and were tagged at the end with the letters ‘AL’ (affiliate link) in parentheses.

When I started the experiment I had 2686 followers.

You canÂ download a Microsoft Excel spreadsheet of all 50 tweets with links to the Bit.ly infoÂ here. It’s fairly crude but will allow you to check out the data yourself. Note that the links used during this experiment are still ‘out there’ and the data is likely to change (increase in clicks) over time, so the numbers at Bit.ly likely will differ from what is on this page as the weeks pass.

The Small Print

First of all, I feel I need to point out that this isn’t hard science. It was interesting and fun to undertake and I’m not in any way claiming this is the definitive study. But there is some data of interest here, and it does encourage further thought.

In the Twitter category, I included some links back to articles in this blog.

Sometimes, it was difficult to decide which category a particular link best fit – for example, some videos contain humour. I did the best I could. Obviously there’s a blur between Twitter, social media and tech/internet.

I don’t usually post affiliate links in my Twitter stream, so this was a new thing for my network, and I was curious as to what impact this would have.

The Results

The 50 links had a total of 4937 clicks, and 103 re-tweets. This produces an average per tweet of 98.74 clicks, and 2.06 re-tweets. This equates to a click-through rate of about 3.67 per cent of my network for all links.

Two of my tweets received over 500 clicks. The least amount of clicks for a single tweet was 41.

Three tweets received 12 or more re-tweets.

At the end of the experiment I had 2720 followers – a net gain of 34.

The most popular subject was, perhaps surprisingly, religion, which received a total of 867 clicks, for an average of 173.4 per tweet. It also picked up 28 total re-tweets (5.6 per tweet).

Twitter was the third most-popular subject, with 807 total clicks (161.4 per tweet) and 25 re-tweets (5 per tweet).

These were far and away the stand-out categories. Curiously perhaps, social media and tech/internet ranked near the bottom.

The least popular subject was affiliate links, which totalled only 262 clicks, or 52.4 per tweet, and received only two re-tweets. Nobody complained or said anything at all about these affiliate links. I’m not sure anybody even noticed, to be honest.

The words within the quotation marks represent how I worded that tweet.

It’s worth noting that two of these five links (#3 and #4) are articles on this blog, and three of them are about Twitter, which makes sense – you would expect (and hope) that, to some extent at least, people follow me because they enjoy my posts.

If I throw out the highest and lowest-clicked link in each subject, and then consider the average of the numbers remaining (known as the truncated mean),the data output changes as follows:

Modified Percentage Of Total Clicks (2338)

Modified Total Clicks, Modified Average Clicks

As we can see when we remove the extremes, Twitter is now the stand-out subject, and that makes perfect sense – people on Twitter care about Twitter news.

Religion scoring so highly is fairly surprising but it’s worth noting that all of the links in that category were fairly controversial, and those likely attracted clicks from believers and non-believers.

Conclusion

This was a fun experiment to put together and I found both the process and the results obtained from the work rewarding. As I said at the start, this shouldn’t in any way be considered a scientific study – we can’t make any definitive conclusions from the limited data.

That said, I have received some important feedback here about the kinds of links and content my Twitter network enjoys, and it was fascinating to watch links getting clicked in a live environment, and especially seeing how the ‘ripple effect’ from re-tweets quickly increased that click rate.

If you’re curious about what your followers would like to see from you, you can very easily replicate this experiment yourself – just head on over to Bit.ly, sign up for an account, and start linking away.